# Copyright (c) 2024 Intel Corporation
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#      http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import tensorflow as tf

from examples.tensorflow.common.object_detection.utils import input_utils


def process_source_id(source_id):
    """Processes source_id to the right format."""
    if source_id.dtype == tf.string:
        source_id = tf.cast(tf.strings.to_number(source_id), tf.int32)
    with tf.control_dependencies([source_id]):
        source_id = tf.cond(
            pred=tf.equal(tf.size(input=source_id), 0),
            true_fn=lambda: tf.cast(tf.constant(-1), tf.int32),
            false_fn=lambda: tf.identity(source_id),
        )
    return source_id


def pad_groundtruths_to_fixed_size(gt, n):
    """Pads the first dimension of groundtruths labels to the fixed size."""
    gt["boxes"] = input_utils.pad_to_fixed_size(gt["boxes"], n, -1)
    gt["is_crowds"] = input_utils.pad_to_fixed_size(gt["is_crowds"], n, 0)
    gt["areas"] = input_utils.pad_to_fixed_size(gt["areas"], n, -1)
    gt["classes"] = input_utils.pad_to_fixed_size(gt["classes"], n, -1)
    return gt
